code: def test_two_layers(self):
      shape = (1, 3)
      input_data = np.random.normal(size=shape)
      with tf.name_scope("TFE"):
          model = Sequential()
          model.add(Dense(2, batch_input_shape=shape))
          model.add(Dense(3))
  
          x = tfe.define_private_variable(input_data)
          model(x)
  
file_path: tf-encrypted/tf_encrypted/keras/models/sequential_test.py
imports: import unittest
  import numpy
  import tensorflow
  import tf_encrypted
  from tf_encrypted.keras import Sequential
  from tf_encrypted.keras.layers import Dense
label_desc: Use image node_id 1 for calling the TestSequential obj's underlying member method code with example usage: obj.test_two_layers() without return types